Predicting Climate Change Impacts on the Rare and Endangered Horsfieldia tetratepala in China

Population status, habitat preferences and predictive current and future distributions of three endangered Silene species under changing climate

One of the most crucial steps in the practical conservation of endangered endemic mountain plants is to address their population size status and habitat requirements concurrently with understanding their response to future global warming. Three endangered Silene species-Silene leucophylla Boiss., S. schimperiana Boiss., and S. oreosinaica Chowdhuri-in Egypt were the focus of the current study. These species were examined for population status change, habitat quality variables (topography, soil features, and threats), and predictive current and future distributions. To find population size changes, recent field surveys and historical records were compared. Using Random Forest (RF) and Canonical Correspondence Analysis (CCA), habitat preferences were assessed. To forecast present-day distribution and climate change response, an ensemble model was used. The results reported a continuous decline in the population size of the three species. Both RF and CCA addressed that elevation, soil texture (silt, sand, and clay fractions), soil moisture, habitat-type, chlorides, electric conductivity, and slope were among the important variables associated with habitat quality. The central northern sector of the Saint Catherine area is the hotspot location for the predictive current distribution of three species with suitable areas of 291.40, 293.10, and 58.29 km2 for S. leucophylla, S. schimperiana, and S. oreosinaica, respectively. Precipitation-related variables and elevation were the key predictors for the current distribution of three Silene species. In response to climate change scenarios, the three Silene species exhibited a gradual contraction in the predictive suitable areas with upward shifts by 2050 and 2070. The protection of these species and reintroduction to the predicted current and future climatically suitable areas are urgent priorities. Ex-situ conservation and raised surveillance, as well as fenced enclosures may catapult as promising and effective approaches to conserving such threatened species.

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

Climate change has significantly influenced the growth and distribution of plant species, particularly those with a narrow ecological niche. Understanding climate change impacts on the distribution and spatial pattern of endangered species can improve conservation strategies. The MaxEnt model is widely applied to predict species distribution and environmental tolerance based on occurrence data. This study investigated the suitable habitats of the endangered Ormosia microphylla in China and evaluated the importance of bioclimatic factors in shaping its distribution. Occurrence data and environmental variables were gleaned to construct the MaxEnt model, and the resulting suitable habitat maps were evaluated for accuracy. The results showed that the MaxEnt model had an excellent simulation quality (AUC = 0.962). The major environmental factors predicting the current distribution of O. microphylla were the mean diurnal range (bio2) and precipitation of the driest month (bio14). The current core potential distribution areas were concentrated in Guangxi, Fujian, Guizhou, Guangdong, and Hunan provinces in south China, demonstrating significant differences in their distribution areas. Our findings contribute to developing effective conservation and management measures for O. microphylla, addressing the critical need for reliable prediction of unfavorable impacts on the potential suitable habitats of the endangered species.

Predicting Quercus gilva distribution dynamics and its response to climate change induced by GHGs emission through MaxEnt modeling

Quercus gilva, an evergreen tree species in Quercus section Cyclobalanopsis, is an ecologically and economically valuable species in subtropical regions of East Asia. Predicting the impact of climate change on potential distribution of Q. gilva can provide a scientific basis for the conservation and utilization of its genetic resources, as well as for afforestation. In this study, 74 distribution records of Q. gilva and nine climate variables were obtained after data collection and processing. Current climate data downloaded from WorldClim and future climate data predicted by four future climate scenarios (2040s SSP1-2.6, 2040s SSP5-8.5, 2060s SSP1-2.6, and 2060s SSP5-8.5) mainly based on greenhouse gases emissions of distribution sites were used in MaxEnt model with optimized parameters to predict distribution dynamics of Q. gilva and its response to climate change. The results showed that the predicted current distribution was consistent with natural distribution of Q. gilva, which was mainly located in Hunan, Jiangxi, Zhejiang, Fujian, Guizhou, and Taiwan provinces of China, as well as Japan and Jeju Island of South Korea. Under current climate conditions, precipitation factors played a more significant role than temperature factors on distribution of Q. gilva, and precipitation of driest quarter (BIO17) is the most important restriction factor for its current distribution (contribution rate of 57.35%). Under future climate conditions, mean temperature of driest quarter (BIO9) was the essential climate factor affecting future change in potential distribution of Q. gilva. As the degree of climatic anomaly increased in the future, the total area of predicted distribution of Q. gilva showed a shrinking trend (decreased by 12.24%-45.21%) and Q. gilva would migrate to high altitudes and latitudes. The research results illustrated potential distribution range and suitable climate conditions of Q. gilva, which can provide essential theoretical references for the conservation, development, and utilization of Q. gilva and other related species.